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WO2005125179A1 - Dispositif de traitement d’image accentuant la texture, programme de traitement d’image, caméra électronique et méthode de traitement d’image - Google Patents

Dispositif de traitement d’image accentuant la texture, programme de traitement d’image, caméra électronique et méthode de traitement d’image Download PDF

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Publication number
WO2005125179A1
WO2005125179A1 PCT/JP2005/011327 JP2005011327W WO2005125179A1 WO 2005125179 A1 WO2005125179 A1 WO 2005125179A1 JP 2005011327 W JP2005011327 W JP 2005011327W WO 2005125179 A1 WO2005125179 A1 WO 2005125179A1
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WO
WIPO (PCT)
Prior art keywords
image processing
component
texture
unit
smoothing
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/JP2005/011327
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English (en)
Japanese (ja)
Inventor
Hideyasu Kuniba
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Nikon Corp
Original Assignee
Nikon Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Nikon Corp filed Critical Nikon Corp
Priority to US11/629,794 priority Critical patent/US7924288B2/en
Priority to EP05753504.9A priority patent/EP1775936A4/fr
Priority to JP2006514831A priority patent/JP4595939B2/ja
Publication of WO2005125179A1 publication Critical patent/WO2005125179A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/73—Deblurring; Sharpening
    • G06T5/75—Unsharp masking
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/90—Dynamic range modification of images or parts thereof
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N1/00—Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
    • H04N1/46—Colour picture communication systems
    • H04N1/56—Processing of colour picture signals
    • H04N1/58—Edge or detail enhancement; Noise or error suppression, e.g. colour misregistration correction
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10024—Color image

Definitions

  • Image processing apparatus image processing program, electronic camera, and image processing method for enhancing texture
  • the present invention relates to an image processing technique for enhancing the texture of a subject in an image.
  • Patent Document 1 is known as a device for compensating for such a decrease in texture.
  • Patent Document 1 a minute amplitude component is extracted from image data, and the minute amplitude component is added to the image data.
  • this conventional technology it is possible to enhance the texture such as so-called “shortening”.
  • Patent document 1 Japanese Patent Application Laid-Open No. 2001-118064 (eg, FIG. 5)
  • an object of the present invention is to provide an image processing technique that emphasizes the texture of an image while preventing the noise feeling from deteriorating.
  • An image processing apparatus of the present invention is an image processing apparatus that performs image processing on image data including luminance information and color information, and includes the following fluctuation extracting unit, converting unit, and adding unit.
  • the fluctuation extracting unit extracts a local fluctuation component from the color information of the image data.
  • the conversion unit generates a texture component of the luminance information in a pseudo manner from the fluctuation component of the color information.
  • the adding unit adds the generated texture component to the luminance information.
  • the fluctuation extracting unit includes a smoothing unit and a difference unit.
  • the smoothing unit performs a smoothing process on the image data and extracts a smoothing component.
  • the difference unit obtains a local fluctuation component from the difference between the image data and the smoothed component.
  • the conversion unit converts the conversion unit
  • the texture component is generated by modulating the variation component according to the value of the smoothing component.
  • the conversion unit modulates the fluctuation component according to the random number value to generate the texture component.
  • the conversion unit generates a texture component of the luminance information in a pseudo manner by modulating the “variation component of the color information” according to the luminance information.
  • the variation extraction unit includes a first smoothing unit, a second smoothing unit, and a difference unit.
  • the first smoothing unit smoothes a spatial frequency band having high visual sensitivity.
  • the second smoothing unit smoothes a noise band.
  • the difference unit generates a fluctuation component by taking a difference before and after the smoothing by the first smoothing unit.
  • the adding unit adds the generated texture component to the output of the second smoothing unit.
  • An electronic camera includes the image processing device according to any one of the above ⁇ 1> to ⁇ 5>, and an imaging unit that captures an image of a subject and generates image data.
  • the image data generated by the imaging unit is processed by the image processing device.
  • the image processing program according to the present invention controls the computer according to any one of the above ⁇ 1> to ⁇ 5>. And a function as the fluctuation extracting unit, the converting unit, and the adding unit.
  • An image processing method is an image processing method for performing image processing on image data including luminance information and color information, and executes the following operation steps.
  • variation extracting step a local variation component of the color information power of the image data is extracted.
  • a texture component of luminance information is pseudo-generated from a variation component of color information.
  • the generated texture component is added to the luminance information.
  • a local fluctuation component is extracted from color information of image data.
  • This fluctuation component includes important detail information that determines the texture expression of the image. Therefore, a texture component of the luminance information is generated in a pseudo manner by using the variation component of the color information as a detail material. The pseudo texture component generated from the color information is added to the luminance information. Through such processing, it is possible to reflect the change in the color information on the texture component of the luminance information, and to enrich the texture expression of the luminance information.
  • the pseudo texture component generated by the color information force is increased or decreased according to the brightness of the luminance information.
  • this processing it is possible to increase the amount of addition of the pseudo texture component in the gradation region where noise is not conspicuous, and to reduce the addition amount of the pseudo texture component in the gradation region where noise is conspicuous. In this case, it is possible to generate an image with less noise and rich texture.
  • the pseudo texture component generated from the color information is increased or decreased according to the signal level of the color information.
  • this processing it is possible to increase the amount of pseudo texture components added in the low saturation region where the texture is not conspicuous, and to reduce the amount of pseudo texture components added in the high saturation region where the noise is conspicuous. . In this case, it is possible to generate an image with little color noise and rich texture.
  • the fluctuation component of the color information is subjected to random number modulation.
  • the frequency component of the fluctuation component can be frequency-spread (or the frequency can be converted to a higher frequency).
  • the texture included in the variation component of the color information changes randomly and finely, resulting in a grain close to the real thing. A small change in texture can be added to the output image.
  • this random number modulation it is possible to spread the frequency of low-frequency concentrated noise (so-called color spots) included in the fluctuation component of color information.
  • low-frequency concentrated noise such as spots is also eliminated from the pseudo-texture component, and the pseudo-texture component can be changed to a small-grain texture component. In this case, speckles and noticeable noise are reduced, and an image with a rich texture can be generated.
  • FIG. 1 is a flowchart illustrating an operation of the first embodiment.
  • FIG. 2 is a flowchart illustrating the operation of the second embodiment.
  • FIG. 3 is a block diagram showing a configuration of an electronic camera.
  • FIG. 1 is a flowchart illustrating an image processing program according to the first embodiment.
  • the computer captures the input image Vo to be processed.
  • the computer performs the following smoothing processing on the input image Vo to obtain a smoothed image VI.
  • (x, y) and (x ', y') in this expression are coordinates indicating the pixel position of the image.
  • ⁇ in this equation is a value that determines the amplitude range in which the smoothing is performed strongly, and It is preferable to set the amplitude to about the amplitude of the rule component.
  • R in the equation is a value that determines the radius of the smoothing, and it is preferable to set the radius to about the noise radius and the detail radius.
  • the weighting function W (d) does not have to be the above equation, but is preferably a monotonically decreasing function of the pixel difference
  • the computer obtains a fluctuation component Vh in the input image Vo by taking a difference between the input image Vo and the smoothing image VI.
  • Vh Vo (x, y) -Vl (x, y)... [2]
  • the computer branches the operation in accordance with the “variable component Vh processing modes 1 to 3” custom-set by the user in advance.
  • the computer multiplies the fluctuation component Vh by a proportional constant k smaller than 1 to generate a texture component Vh '.
  • Vh '(x, y) k-Vh (x, y)... [3]
  • the computer modulates the fluctuation component Vh in accordance with the global brightness indicated by the smoothed image VI using the following equation.
  • Step S7 is the upper limit of the pixel value, and is set to, for example, 255. After this processing, the computer shifts the operation to Step S8. [0024] Step S7:
  • the computer obtains the texture component V by multiplying the fluctuation component Vh by, for example, a random number S in the section [0, 1] or the section [ ⁇ 1, 1].
  • Vh '(x, y) S -Vh (x, y)... [5]
  • the random number S may be, for example, a random number such as white noise or a random number such as lZf noise.
  • the computer calo-calculates the processed texture component VI into the smoothed image VI according to the following formula to obtain an output image V2.
  • V2 (x, y) Vl (x, y) + Vh (x, y)... [6]
  • the fluctuation component is largely amplitude-modulated in the dark region of the smoothing image VI.
  • the texture is not conspicuous, and it is possible to obtain an output image V2 with a rich texture.
  • the fluctuation component is small and amplitude-modulated in the middle to bright regions where noise is noticeable. Therefore, an output image V2 with less noticeable noise can be obtained.
  • the fluctuation component is modulated by random numbers.
  • the spatial frequency of the fluctuation component can be spread.
  • the texture included in the fluctuation component changes randomly, and it is easy to give the output image V2 a randomly changed texture close to the real thing.
  • the noise contained in the fluctuation component is subjected to random number modulation to spread the spatial frequency component of the noise over a wide area.
  • noise that gives a noticeable impression is caused by noise biased to a specific spatial frequency band. Therefore, by using mode 3 to spread this noise in frequency, it is possible to eliminate noise concentration in a specific spatial frequency band, and to change the noise to small and less noticeable noise.
  • FIG. 2 is a flowchart illustrating an image processing program according to the second embodiment.
  • the operation of the second embodiment by the computer will be described along the step numbers shown in FIG.
  • the computer fetches an input image to be processed and obtains luminance information Lo and color information ao, bo of the input image.
  • the computer performs the following smoothing processing on the input image (Lo, ao, bo) to obtain a smoothed image (Ll, al, bl).
  • equations [9] and [11] may be implemented stepwise. In these equations [9] and [11], the smoothing process is executed in two stages of the horizontal and vertical directions of the screen.
  • the value der to determine the stronger subjected amplitude range blunt I spoon is, the amplitude of the noise amplitude to detail component It is preferable to set to about.
  • R in the formula is a value that determines the radius of the smoothing, and is preferably set to be about the noise radius or the detail radius.
  • weighting functions W, Wx, Wy do not have to be the above equations, but are preferably a monotonically decreasing function of the pixel difference
  • d a monotonically decreasing function of the weighting functions W, Wx, and Wy.
  • the computer takes the difference between the input image (Lo, ao, bo) and the smoothed image (Ll, al, bl) to calculate the fluctuation component (Lh , ah, bh).
  • ah (x, y) ao, x, y) —al, x, y)
  • the computer branches the operation in accordance with the “variable component (Lh, ah, bh) processing modes 1 to 3” which are custom-set by the user in advance.
  • the computer shifts the operation to step S25.
  • the computer shifts the operation to step S26.
  • the computer simulates the texture component Vh 'of the luminance information by weighted addition of the fluctuation component Lh of the luminance information and the fluctuation components ah and bh of the color information at a weight ratio (kl, ka, kb). Generated.
  • Vh '(x, y) klLh (x, y) + kaah (x, y) + kbbh (x, y)
  • the weighting ratio ka, kb of the color information can be determined by considering the visual effects of the fluctuation components ah, bh of the color information on the luminance (particularly the texture). It is preferable to make a decision through a subjective test or the like.
  • the computer performs modulation processing on the fluctuation component Lh of the luminance information and the fluctuation components ah and bh of the color information in accordance with the global brightness indicated by the luminance information L1 using the following equation.
  • Vh ' ⁇ x, y) t (Ll (x, y)) (Lh (x, y) + ah (x, y) + bh (x, y))
  • Vh '(x, y) t ⁇ L ⁇ ⁇ x, y)) Lh (x, nu) + tc (al (x, y), bl (x, j X "W, y) + bh ⁇ x , y)) ⁇ ⁇ ⁇ [18]
  • Amax and bmax in the equations are the upper limits of the color information al and bl.
  • step S28 After thus generating the texture component V of the luminance information in a pseudo manner, the computer shifts its operation to step S28.
  • the computer In this mode 3, the computer generates random numbers S 1 to S 3 in the section [0, 1] or the section [ ⁇ 1, 1] for the fluctuation component Lh of the luminance information and the fluctuation components ah, bh of the color information. Respectively By multiplying, the texture component VI of the luminance information is pseudo-generated.
  • Vh '(x, y) SILh (x, y) + S2ah (x, y) + S3bh (x, y)
  • the random numbers S1 to S3 may be random numbers such as white noise, or random numbers such as 1 Zf noise.
  • the computer adds the processed texture component VI to the luminance information L1 of the smoothed image according to the following equation to obtain an output image (L2, al, bl).
  • the texture component of the luminance information is pseudo-generated by multiplying the fluctuation components ah, bh of the color information al, bl by a predetermined ratio.
  • the change in color information can be reflected on the texture component of the luminance information, and the texture of the output image can be enriched.
  • the fluctuation component is largely amplitude-modulated in a dark region of the luminance information L1 after smoothing.
  • the texture can be particularly emphasized in a dark area where the texture is not conspicuous, and an output image with a rich texture can be obtained.
  • the amplitude of the fluctuation component is small-modulated in the middle to bright regions where noise is conspicuous. Therefore, an output image with less noticeable noise can be obtained.
  • the texture can be emphasized in a low-saturation area where the texture is not conspicuous, and an output image with a rich texture can be obtained.
  • the amplitude of the fluctuation component is small-modulated in the middle to high chroma region where noise is conspicuous. Therefore, an output image with less noticeable noise can be obtained.
  • the frequency component of the fluctuation component can be frequency-spread.
  • the texture included in the fluctuation component changes randomly and finely, and the texture that is randomly changed close to the real thing is added to the output image. It becomes possible to do.
  • a kind of dither effect can be added by adding the texture component Vh ′ that has been subjected to random number modulation. As a result, the gradation of the output image can be appropriately increased.
  • the variation component of the color information is converted into a texture component of the luminance information and added to the luminance information. Therefore, the color noise does not deviate.
  • the third embodiment is an embodiment of an electronic camera.
  • FIG. 3 is a block diagram showing the configuration of the present embodiment.
  • a photographing lens 12 is attached to an electronic camera 11.
  • the light receiving surface of the image sensor 13 is arranged in the image space of the taking lens 12.
  • the operation of the image sensor 13 is controlled by the output pulse of the timing generator 22b.
  • the image generated by the image sensor 13 is temporarily stored in the knocker memory 17 via the AZD converter 15 and the signal processor 16.
  • This buffer memory 17 is connected to a bus 18.
  • An image processing unit 19, a card interface 20, a microprocessor 22, a compression / decompression unit 23, and an image display unit 24 are connected to the bus 18.
  • the card interface 20 reads and writes data from and to the removable memory card 21.
  • the microprocessor 22 includes an electronic camera 11 A user operation signal is input from the switch group 22a. Further, the image display unit 24 displays an image on a monitor screen 25 provided on the back of the electronic camera 11.
  • the microprocessor 22 and the image processing unit 19 perform the texture enhancement (FIGS. 1 and 2 and the like) of the first and second embodiments.
  • Such texture enhancement may be performed on the image data at the time of imaging, or may be performed later on the image data recorded on the memory card 21.
  • an image processing server on the Internet may provide an image processing method as shown in FIGS. 1 and 2 as a service to image data transmitted from a user.
  • the texture enhancement is performed in the Lab color space.
  • the present invention is not limited to this.
  • similar texture enhancement may be performed in the HSV color space or other color spaces.
  • texture emphasis may be performed only on a part of the screen (a main subject, a person or a skin color region, a shaded portion, a trimming range, a background portion excluding a person or a skin color region, and the like).
  • a part of the screen a main subject, a person or a skin color region, a shaded portion, a trimming range, a background portion excluding a person or a skin color region, and the like.
  • the emphasis on the texture of the luminance is enhanced in the black and white portions and the low chroma portions.
  • the present invention is not limited to this. In general, it is preferable to determine a luminance region or a saturation region that enhances the texture while taking into account the adverse effect of an increase in noise.
  • one type of smoothing processing is performed.
  • a high-quality texture component can be generated by extracting the fluctuation component from the difference before and after the first smoothing process.
  • the texture component, for which the power of the fluctuation component is also obtained to the output of the second low-noise smoothing process, an output image with a high texture and a small noise can be obtained.
  • the present invention is a technique that can be used for an image processing program, an electronic camera, and the like.

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Image Processing (AREA)
  • Picture Signal Circuits (AREA)
  • Facsimile Image Signal Circuits (AREA)
  • Color Image Communication Systems (AREA)

Abstract

Dispositif de traitement d’image qui extrait une composante de variation locale d’information de couleur dans des données image. En utilisant la composante de variation de l’information de couleur, une composante de pseudo-texture d’information de luminosité est produite. La composante de pseudo-texture ainsi produite est ajoutée à l’information de luminosité. Une image possédant une texture améliorée est produite grâce à ce traitement d’image.
PCT/JP2005/011327 2004-06-22 2005-06-21 Dispositif de traitement d’image accentuant la texture, programme de traitement d’image, caméra électronique et méthode de traitement d’image Ceased WO2005125179A1 (fr)

Priority Applications (3)

Application Number Priority Date Filing Date Title
US11/629,794 US7924288B2 (en) 2004-06-22 2005-06-21 Image processing device emphasizing on texture, image processing program, electronic camera, and image processing method
EP05753504.9A EP1775936A4 (fr) 2004-06-22 2005-06-21 Dispositif de traitement d"image accentuant la texture, programme de traitement d"image, caméra électronique et méthode de traitement d"image
JP2006514831A JP4595939B2 (ja) 2004-06-22 2005-06-21 質感を強調する画像処理装置、画像処理プログラム、電子カメラ、および画像処理方法

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JP2004-184208 2004-06-22
JP2004184208 2004-06-22

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EP (1) EP1775936A4 (fr)
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WO2007097125A1 (fr) 2006-02-27 2007-08-30 Nikon Corporation Dispositif de traitement d'image pour corriger une perception massive d'image, programme et procede de traitement d'image, et camera electronique
JP2011022656A (ja) * 2009-07-13 2011-02-03 Nikon Corp 画像処理装置及び画像処理プログラム
JP2012222616A (ja) * 2011-04-08 2012-11-12 Nikon Corp 画像処理装置、撮像装置およびプログラム

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2007097125A1 (fr) 2006-02-27 2007-08-30 Nikon Corporation Dispositif de traitement d'image pour corriger une perception massive d'image, programme et procede de traitement d'image, et camera electronique
EP1991008A4 (fr) * 2006-02-27 2012-04-18 Nikon Corp Dispositif de traitement d'image pour corriger une perception massive d'image, programme et procede de traitement d'image, et camera electronique
JP2011022656A (ja) * 2009-07-13 2011-02-03 Nikon Corp 画像処理装置及び画像処理プログラム
JP2012222616A (ja) * 2011-04-08 2012-11-12 Nikon Corp 画像処理装置、撮像装置およびプログラム

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JPWO2005125179A1 (ja) 2008-04-17
JP4595939B2 (ja) 2010-12-08
EP1775936A1 (fr) 2007-04-18
EP1775936A4 (fr) 2016-05-11
US7924288B2 (en) 2011-04-12
US20070252845A1 (en) 2007-11-01

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